[[validate_dataset]]
path = "dataloader.Dataset"

[validate_dataset.args]
librispeech_dir = "~/data/LibriSpeech/LibriSpeech"
librispeech_metadata_fpath = "/home/xhao/proj/audiozen/recipes/librimix_sot/local/metadata/LibriSpeech/train-clean-100-24K.csv"
duration = 6.0
sr = 24000
num_samples = 10
[validate_dataset.dataloader]
batch_size = 1
num_workers = 1

[meta]
save_dir = "exp"
description = "Train a model using Generative Adversarial Networks (GANs)"
seed = 20220815
exp_id = "swin_default_LR1e-4_AR-NAR"
config_path = "/fred/oz325/xhao/proj/audiozen/recipes/librimix_sot/tokenizer_separation/conf/swin_default_LR1e-4_AR-NAR.toml"

[trainer]
path = "trainer.Trainer"

[loss_function]
path = "torch.nn.MSELoss"

[optimizer]
path = "torch.optim.AdamW"

[model]
path = "model_ar_nar.Model"

[acoustics]
n_fft = 512
hop_length = 128
win_length = 512
sr = 24000

[train_dataset]
path = "dataloader.Dataset"

[test_dataset]
path = "dataloader.Dataset"

[trainer.args]
debug = false
max_steps = 0
max_epochs = 1000
max_grad_norm = 1.0
save_max_score = true
save_ckpt_interval = 5
max_patience = 200
plot_norm = true
validation_interval = 200
max_num_checkpoints = 100
scheduler_name = "constant_schedule_with_warmup"
warmup_steps = 1000
warmup_ratio = 0.0
gradient_accumulation_steps = 1

[loss_function.args]

[optimizer.args]
lr = 0.0001

[model.args]

[train_dataset.args]
librispeech_dir = "~/data/LibriSpeech/LibriSpeech"
librispeech_metadata_fpath = "/home/xhao/proj/audiozen/recipes/librimix_sot/local/metadata/LibriSpeech/train-clean-100-24K.csv"
duration = 6.0
sr = 24000

[train_dataset.dataloader]
batch_size = 20
num_workers = 10
drop_last = true
pin_memory = true

[test_dataset.args]
librispeech_dir = "~/data/LibriSpeech/LibriSpeech"
librispeech_metadata_fpath = "/home/xhao/proj/audiozen/recipes/librimix_sot/local/metadata/LibriSpeech/train-clean-100-24K.csv"
duration = 6.0
sr = 24000
num_samples = 10

[test_dataset.dataloader]
batch_size = 1
num_workers = 1